72.045 - Teaching STEM and Data Science Both in and out of Schools

Session Type: Symposium

Abstract

This symposium will explore insights across in-school and out-of-school programs designed to redress inequalities in learning about data science and STEM fields. Participants include practitioners and collaborating researchers who are studying teaching and learning within formal and informal settings. The presenters will describe and contrast models addressing: What scaffolds can support youth to discover and explore interests related to data science and STEM? What instructional practices and uses of technology can develop young people’s capacities to engage in data-informed practices? What are the barriers to youth participation in STEM and data science learning? What are the affordances and limitations of formal and informal environments? What are the challenges, opportunities, and risks of bridging STEM learning across formal and informal environments?

Sub Unit

• SIG-Technology as an Agent of Change in Teaching and Learning

Chair

• Christopher J. Dede, Harvard University

Papers

• Black Girls Code: Supporting the Development of Technology Skills Among African American Girls - Molly Reisman

• Youth Radio: Student-Driven Data Science Learning - Alexander M. Gurn, Rockman et al

• Technovation: Global Program for the Development of Technology and Entrepreneurial Skills and Self-Efficacy for Girls - Scott Burg, Rockman et al

• San Francisco Unified School District: Equity Imperative to Transform Computer Science - Bryan Twarek, San Francisco Unified School District

Discussant

• Kathleen Tyner, University of Texas at Austin